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A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

ABSTRACT: As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

SUBMITTER: Kim S

PROVIDER: S-EPMC6399057 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

Kim Sehee S Wang Miao M Tyrer Jonathan P JP Jensen Allan A Wiensch Ashley A Liu Gang G Lee Alice W AW Ness Roberta B RB Salvatore Maxwell M Tworoger Shelley S SS Whittemore Alice S AS Anton-Culver Hoda H Sieh Weiva W Olson Sara H SH Berchuck Andrew A Goode Ellen L EL Goodman Marc T MT Doherty Jennifer Anne JA Chenevix-Trench Georgia G Rossing Mary Anne MA Webb Penelope M PM Giles Graham G GG Terry Kathryn L KL Ziogas Argyrios A Fortner Renée T RT Menon Usha U Gayther Simon A SA Wu Anna H AH Song Honglin H Brooks-Wilson Angela A Bandera Elisa V EV Cook Linda S LS Cramer Daniel W DW Milne Roger L RL Winham Stacey J SJ Kjaer Susanne K SK Modugno Francesmary F Thompson Pamela J PJ Chang-Claude Jenny J Harris Holly R HR Schildkraut Joellen M JM Le Nhu D ND Wentzensen Nico N Trabert Britton B Høgdall Estrid E Huntsman David D Pike Malcolm C MC Pharoah Paul D P PDP Pearce Celeste Leigh CL Mukherjee Bhramar B

International journal of cancer 20190120 9

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interact ...[more]

PMID: 30499236

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Project description:Genome-wide association studies (GWASs) have reported numerous associations between risk variants and Alzheimer's disease (AD). However, these associations do not necessarily indicate a causal relationship. If the risk variants can be demonstrated to be biologically functional, the possibility of a causal relationship would be increased. In this article, we reviewed all of the published GWASs to extract the genome-wide significant (p < 5×10-8) and replicated associations between risk variants and AD or AD-biomarkers. The regulatory effects of these risk variants on the expression of a novel class of non-coding RNAs (piRNAs) and protein-coding RNAs (mRNAs), the alteration of proteins caused by these variants, the associations between AD and these variants in our own sample, the expression of piRNAs, mRNAs and proteins in human brains targeted by these variants, the expression correlations between the risk genes and APOE, the pathways and networks that the risk genes belonged to, and the possible long non-coding RNAs (LncRNAs) that might regulate the risk genes were analyzed, to investigate the potential biological functions of the risk variants and explore the potential mechanisms underlying the SNP-AD associations. We found replicated and significant associations for AD or AD-biomarkers, surprisingly, only at 17 SNPs located in 11 genes/snRNAs/LncRNAs in eight genomic regions. Most of these 17 SNPs enriched some AD-related pathways or networks, and were potentially functional in regulating piRNAs and mRNAs; some SNPs were associated with AD in our sample, and some SNPs altered protein structures. Most of the protein-coding genes regulated by the risk SNPs were expressed in human brain and correlated with APOE expression. We conclude that these variants were most robust risk markers for AD, and their contributions to AD risk was likely to be causal. As expected, APOE and the lipoprotein metabolism pathway possess the highest weight among these contributions.

Dataset Information

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

Publications

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

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